Qualitative and Quantitative Assessment of the SET HASDM Database

Licata, Richard J.; Mehta, Piyush M.; Tobiska, W. Kent; Bowman, Bruce R.; Pilinski, M.

doi:10.1029/2021sw002798

Cited by 22 publications

(41 citation statements)

References 52 publications

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“…Our results show that 1) JB2008 and HASDM densities agree moderately well with observations during pre-storm periods; 2) JB2008 underestimates and HASDM overestimates densities during storm main phase, and 3) HASDM estimates agree remarkably well with observations during storm recovery, reproducing cooling effects quite well, but JB2008 density levels always surpass observations during the recovery phase. Licata et al (2021b) noted similar trends when comparing CHAMP and GRACE observations with HASDM and JB2008 results for the Halloween storms. Panel e shows the relative errors of the model estimates with respect to observations.…”

Section: Comparing Model Performance During the Extreme Events Observed By Champ And Gracesupporting

confidence: 56%

“…Typically, 75 calibration satellites are used to fit and correct the JB2008 density and the greater the number of calibration satellites, the higher the accuracy. Because HASDM is able to mitigate uncertainty in atmospheric effects, by resolving the differences between calibration satellites and the core JB2008 model at each epoch (time step), real-time nowcasting specification of the LEO drag environment has improved significantly (e.g., Storz et al, 2005;Bowman et al, 2008;Licata et al, 2021b;Calabia and Jin, 2021).…”

Section: Modelsmentioning

confidence: 99%

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The Current State and Future Directions of Modeling Thermosphere Density Enhancements During Extreme Magnetic Storms

Oliveira

Zesta

Mehta

et al. 2021

Front. Astron. Space Sci.

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Satellites, crewed spacecraft and stations in low-Earth orbit (LEO) are very sensitive to atmospheric drag. A satellite’s lifetime and orbital tracking become increasingly inaccurate or uncertain during magnetic storms. Given the planned increase of government and private satellite presence in LEO, the need for accurate density predictions for collision avoidance and lifetime optimization, particularly during extreme events, has become an urgent matter and requires comprehensive international collaboration. Additionally, long-term solar activity models and historical data suggest that solar activity will significantly increase in the following years and decades. In this article, we briefly summarize the main achievements in the research of thermosphere response to extreme magnetic storms occurring particularly after the launching of many satellites with state-of-the-art accelerometers from which high-accuracy density can be determined. We find that the performance of an empirical model with data assimilation is higher than its performance without data assimilation during all extreme storm phases. We discuss how forecasting models can be improved by looking into two directions: first, to the past, by adapting historical extreme storm datasets for density predictions, and second, to the future, by facilitating the assimilation of large-scale thermosphere data sets that will be collected in future events. Therefore, this topic is relevant to the scientific community, government agencies that operate satellites, and the private sector with assets operating in LEO.

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Section: Comparing Model Performance During the Extreme Events Observed By Champ And Gracesupporting

confidence: 56%

Section: Modelsmentioning

confidence: 99%

The Current State and Future Directions of Modeling Thermosphere Density Enhancements During Extreme Magnetic Storms

Oliveira

Zesta

Mehta

et al. 2021

Front. Astron. Space Sci.

Self Cite

View full text Add to dashboard Cite

show abstract

“…Our results show that (i) JB2008 and HASDM densities agree moderately well with observations during pre-storm periods; (ii) JB2008 underestimates and HASDM overestimates densities during storm main phase, and (iii) HASDM estimates agree remarkably well with observations during storm recovery, reproducing cooling effects quite well, but JB2008 density levels always surpass observations during the recovery phase. Licata et al (2021b) noted similar trends when comparing CHAMP and GRACE observations with HASDM and JB2008 results for the Halloween storms. Panel e shows the relative errors of the model estimates with respect to observations.…”

Section: Comparing Model Performance During the Extreme Events Observ...supporting

confidence: 56%

Section: Modelsmentioning

confidence: 99%

The current state and future directions of modeling thermosphere density enhancements during extreme magnetic storms

Oliveira,

Zesta,

Mehta

et al. 2021

Preprint

Self Cite

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Satellites, crewed spacecraft and stations in low-Earth orbit (LEO) are very sensitive to atmospheric drag. A satellite's lifetime and orbital tracking become increasingly inaccurate or uncertain during magnetic storms. Given the planned increase of government and private satellite presence in LEO, the need for accurate density predictions for collision avoidance and lifetime optimization, particularly during extreme events, has become an urgent matter and requires comprehensive international collaboration. Additionally, long-term solar activity models and historical data suggest that solar activity will significantly increase in the following years and decades. In this article, we briefly summarize the main achievements in the research of thermosphere response to extreme magnetic storms occurring particularly after the launching of many satellites with state-of-the-art accelerometers from which high-accuracy density can be determined. We find that the performance of an empirical model with data assimilation is higher than its performance without data assimilation during all extreme storm phases. We discuss how

show abstract

“…Oftentimes the integrated densities from HASDM are slightly greater than those from EXTEMPLAR. In a comparison between the SET HASDM data set with the JB2008 model and CHAMP and GRACE density measurements, Licata et al (2021) had found that the HASDM density values were also consistently greater than the values derived from the CHAMP and GRACE accelerometer measurements, while matching better than the JB2008 model. Licata et al (2021) also found that during the major storm in October 2003 (the same event shown here in the first half of Figure 6), while the HASDM data set had slightly larger densities than measured with CHAMP GRACE, it did very well at matching the relative changes in density during this period.…”

Section: Discussionmentioning

confidence: 96%

Comparison of a Neutral Density Model With the SET HASDM Density Database

et al. 2021

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A major focus of space weather research has been on the topic of the mass density of the neutral atoms and molecules in the thermosphere. As the variations in this density perturb the orbital motion of satellites, there has been considerable effort in being able to predict these variations using both empirical models and numerical simulations (Bruinsma et al., 2018;Emmert, 2015).Recently Weimer et al. (2020) had described a new empirical model that calculated exospheric temperatures, the asymptotic limit that the temperature in the thermosphere reaches at high altitudes (Prölss & Bird, 2004), often abbreviated as either T ex or T ∞ . The temperature inputs to the model were derived from neutral density measurements from multiple satellites. Data from the Challenging Mini-satellite Payload (CHAMP) (Bruinsma et al., 2004;Reigber et al., 2002) in the years 2002 through 2009 were used, along with the Gravity Recovery and Climate Experiment (GRACE) satellites (Tapley et al., 2004), from 2003 through 2010. These total mass densities were derived from accelerometer measurements of the orbital drag. In our work we use density data from the CHAMP and GRACE missions provided by Mehta et al. (2017), who had recalibrated the drag coefficients

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Qualitative and Quantitative Assessment of the SET HASDM Database

Abstract: covering almost two solar cycles. 11• HASDM models the movement of lighter species during solar minimum condi-12 tions.

Cited by 22 publications

References 52 publications

The Current State and Future Directions of Modeling Thermosphere Density Enhancements During Extreme Magnetic Storms

The Current State and Future Directions of Modeling Thermosphere Density Enhancements During Extreme Magnetic Storms

The current state and future directions of modeling thermosphere density enhancements during extreme magnetic storms

Comparison of a Neutral Density Model With the SET HASDM Density Database

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